About the Model
Camirrem turns raw baseball data into clear, ranked opportunities — and tracks how those rankings actually perform against real games.
What Camirrem does
Camirrem uses statistical models to rank player opportunities for a given slate. Each player gets an Opportunity Score that reflects how favorable the day looks for them based on a wide set of baseball data points.
What the models look at
Our scoring combines numerous categories of baseball data, including:
- Batter quality and recent form
- Pitcher matchup and handedness
- Career history vs the opposing pitcher
- Ballpark factors
- Weather conditions
- Opposing bullpen quality and recent usage
- Game context (lineup confirmation, batting order)
Each input contributes a measurable amount to the final score. We don't publish the proprietary weights or formulas, but every component is visible in each player's breakdown so you can see what's driving the ranking.
Validated against real results
Every day's rankings are snapshotted and stored. After games are final, results are pulled from MLB and matched back to each snapshot. That means rankings are never silently recalculated — historical performance is locked in at the time the slate was published.
Public performance tracking
Model performance is published openly on the Model Performance page. You can see lifetime hit rates by tier, recent 10-day history, and how the top of the ranking performs versus the slate baseline. Nothing is hidden after the fact.
Models evolve
We test new inputs, retire weak ones, and adjust how components are weighted as we gather more validated results. When the methodology changes meaningfully, historical scores remain attached to the version of the model that produced them.
Informational, not guaranteed
Rankings are a data product. They highlight where the underlying numbers point on a given day. They are not predictions, locks, or guarantees of any outcome, and they are not betting advice. Use them as one input into your own decisions.